Diet and Behavior

The study by Mehlig et al. (2024) aimed to investigate the relationship between eating behavior, as assessed by the Three-Factor Eating Questionnaire (TFEQ), and measures of adiposity in a cross-sectional analysis. A total of 573 women, aged between 38 and 50, who participated in the Gothenburg population study of women in 2016/17 completed the TFEQ-R21. The study examined three aspects of eating behavior, both from an outcome and a predictor aspect of adiposity—emotional eating (EE), uncontrolled eating (UE), and cognitive restraint (CR). All TFEQ domains were favorably correlated with diets, according to the results. CR was connected with a decreased consumption of sweets, but EE and UE were linked to increased consumption. Additionally, there was a negative correlation between well-being and EE and UE. EE and CR (while UE showed no such correlation) were found to be positively associated with various adiposity measures (skinfold thickness, waist-to-hip ratio, waist-to-height ratio, BMI) when considering all domains simultaneously in the models. For instance, a one standard deviation increase in EE was associated with obesity (BMI ≥ 30 kg/m²) and abdominal fat (waist circumference > 88 cm). Remarkably, dieting in the past and present was similarly favorably correlated with these results; however, in mutually adjusted models, there was no significant correlation found between UE and CR. The authors suggest that emotional eating behavior is linked to adiposity in middle-aged women, across a wide range of body fat levels, and independently of dieting behavior. These findings imply that obesity treatment should incorporate psychological support to mitigate the risk of emotional eating in response to negative mood states. [NPID: Eating behavior, adiposity measures, emotional eating, cognitive restraint, dieting behavior, obesity]

This study by Petersen et al. (2024) aimed to investigate the impact of a food-based intervention on changes in the Healthy Eating Index (HEI)-2015 and to explore the relationship between HEI-2015 alterations and the intervention's effects on cardiometabolic risk factors. Conducted as part of the Habitual Diet and Avocado Trial, a multicenter randomized controlled parallel-arm study that lasted twenty-six weeks and included 1008 abdominally obese participants (≥ 25 years of age, waist circumference: males ≥ 40 inches, females ≥ 35 inches). Participants were divided into two groups: a habitual diet group, which maintained their usual dietary habits, and an avocado-supplemented diet group, which consumed one avocado daily. HEI-2015 changes were evaluated through a single 24-hour recall at four time points, and mixed models were utilized for analysis. Analysis of the results demonstrated that avocado supplementation substantially increased HEI-2015 scores at 26 weeks compared to controls. Furthermore, various components of HEI-2015, including fatty acid ratio, total vegetables, sodium, added sugars and refined grains, displayed greater improvements with avocado supplementation. Notably, differences in HEI-2015 enhancements were observed by gender, with females experiencing more significant increases than males in the avocado-supplemented diet group. However, changes in HEI-2015 were not predictive of alterations in cardiometabolic disease risk factors. Overall, the findings suggest that daily avocado consumption for 26 weeks among adults with abdominal obesity can enhance adherence to dietary guidelines. Yet, changes in diet quality do not necessarily correlate with changes in cardiometabolic risk factors. [NPID: Diet quality, cardiometabolic disease, avocado, obesity]

Debate remains on whether interventions focusing on emotion-driven impulsiveness or psychosocial well-being are more effective at reducing unhealthy eating choices. Do et al. (2024) sought to examine the (separate) causal effects of emotion-driven impulsiveness and psychosocial well-being on the inclination for sweet and fat-rich foods in a population of European teenagers. The authors collected self-reported data on fat inclination (range: 0 to 72.6), sweet inclination (score range: 0 to 68.4), psychosocial well-being using the KINDLR Questionnaire, and emotion-driven eagerness using the UPPS-P negative urgency subscale, from a sample of 2065 participants in the IDEFICS/I.Family cohort (mean age: 13.4 years). Moreover, the authors investigated the potential presence of an indirect relationship between psychological well-being and the tendency to be inclined towards fats and sweets, which would be facilitated through emotion-driven impulsiveness. The authors noted that, in the hypothetical scenario where all adolescents possessed high levels of psychosocial well-being relative to poor ones, an average reduction in the inclination for sweet consumption would be observed, in addition to a more modest degree of reduction in the inclination for fats. Likewise, average fat and sweet inclination would decrease if all teenagers had higher levels of emotion-driven impulsiveness than low levels, as seen through the indirect effect of psychosocial well-being via emotion-driven impulsiveness for average sweet and fat inclination. The authors conclude that, regarding their research inquiry, an intervention aimed at emotion-driven impulsiveness would be somewhat more successful in lowering teenagers' inclination toward sweets and fat than those targeting psychosocial well-being. [NPID: Psychosocial well-being, impulsive behavior, dietary factors, food choices, adolescents]

In this work by Longo-Silva et al. (2022), the authors sought to ascertain if the acts of missing breakfast, eating lunch or supper at a later time were cross-sectionally linked to higher BMIs and obesity, in addition to pinpointing circadian-related factors and obesogenic behaviors linked to late-night eating. A virtual environment was used for data gathering in this exploratory population-based study, which included 776 participants. The demographic median for the lunch and dinner timing was utilized to stratify participants into early (lunch prior to 12:34/dinner prior to 20:55) and late (lunch after 12:34/dinner after 20:55) eaters. Participants were divided into breakfast-eaters (first meal before 10:00) and skippers (first meal after 10:00). Analysis of the data revealed that BMI increased by 0.74 kg/m2 for every extra hour spent at lunch. Compared to those who ate breakfast and those who ate lunch early, those who skipped breakfast and those who ate lunch later had increased chances of becoming obese. Age, gender, region, amount of physical activity, and food quality had no bearing on these correlations. No statistically significant changes were discovered in comparing early and late supper eaters. The authors conclude, according to their findings, that eating a late lunch and skipping breakfast are linked to higher BMIs and an increased risk of obesity. Understanding the obesogenic traits and behaviors associated with missing breakfast and eating later in the day may be beneficial for developing future dietary guidelines for treating and preventing obesity. [NPID: Chrono-nutrition, food timing, late eating, obesity, food intake timing]

A healthy diet is paramount to wellbeing, but during the COVID-19 pandemic, it was crucial to strengthen immunity and stave against viral illnesses. However, many reports indicate that maintaining a healthy diet was more of a victim of the epidemic than a strategy for battling it. While little is currently known regarding nutritional consequences, young people faced disproportionate pandemic-related disturbances during a crucial development time. During the COVID-19 shutdown, Parker et al. (2023) used a cross-sectional methodology to investigate dietary inequalities in young adults (ages 18 to 28). A 15-20 minute online survey with questions about attitudes towards healthy eating, food sources and composition, food insecurity, weight change, and physical activity was completed by 254 participants. In addition to comparisons based on gender and family income, the authors investigated the factors that played a role in healthy eating perception, with considerations made for sociodemographic and other influential variables. While there was a definite general tendency towards hazardous behaviors, analysis has also revealed noticeable improvements. For instance, junk food consumption grew dramatically (+ 3%), activity levels dropped by 33%, weight climbed by 40%, and 5-8% of people experienced regular food insecurity. While this happened, fewer people were dining out, and more people were cooking at home. Higher-income participants were disproportionately represented in healthy changes, whereas those with lower incomes were overrepresented in harmful changes. While females reported more weight fluctuations, men reported more considerable changes in food composition. Food insecurity, decreased exercise levels, and weight increase were predictors of poor eating patterns. Living with friends or roommates was associated with better eating, but only among people with lower incomes. The authors recommend that pandemic-minded public health measures should take adverse dietary patterns into consideration, paying close attention to low-income young adults in particular. Instead of focusing primarily on behavioral treatments, solutions should be designed to reshape the economic, social, and physical contexts. [NPID: COVID19, diet, health, inequities, young adults]

Snacking is a typical diet practice that contributes significantly to daily calorie consumption, having a key role in determining the quality of a diet. It is still unknown, nevertheless, how snacking quality, quantity, and timing relate to cardiometabolic health. To answer these questions, Bermingham et al. (2023) used data from the UK PREDICT 1 cohort (n = 1002), including demographics, food, stool metagenomics, and health (fasting and postprandial cardiometabolic blood and anthropometrics indicators). Snacks (food or drink consumed between meals) were self-reported (weighed records) over the course of 2-4 days. The snack diet index (SDI) was used to calculate the average frequency and quality of snacking (N = 854 after exclusions). Data analysis demonstrated that participants were 73% female on average, had a mean BMI of 25.6 kg/m2, and had a mean age of 46.1 ± 11.9 years. 44% of participants did not agree on the quality of their meals and snacks; 95% of participants ate snacks (≥1 snack per day; n = 813); the average daily snack consumption was 2.28 snacks (24 ± 16% of daily calories; 203 ± 170 kcal). Snacking amount and frequency overall were not linked to cardiometabolic risk factors in snackers. Higher blood indicators, such as increased postprandial triglycerides (TGs), fasting TGs, insulin resistance, fasting insulin, and hunger, were linked to worse snack quality (SDI range 1–11). Compared to all other snacking periods, late-evening eating (at or past 9 p.m.; 31%) was related to lower blood indicators (HbA1c, however, remained significant after multiple tests). The authors conclude that using snack timing and quality provides simple targets for dietary quality and health status improvements. [NPID: Snacking, quality, frequency, quantity, timing, cardiometabolic health]

It is hypothesized that how fat is perceived in terms of scent, flavor, and texture affects eating habits, food choices, dietary intake, and, ultimately, long-term health. In this study, Kindleysides et al. (2017) looked at relationships between eating habits, food consumption, body mass index (BMI), fatty acid taste, mouthfeel of fat, and olfaction. To measure the oleic acid taste and olfactory thresholds, the olfactory threshold for n-butanol, and the subjective mouthfeel evaluations of custard samples, fifty women participated in three sessions. A Food Frequency and Three-Factor Eating Questionnaire were each used to assess dietary intake and eating behavior. Analysis of the results revealed that olfactory detection of oleic acid and taste had a favorable correlation, whereas women who are particularly sensitive to oleic acid's flavor have much higher n-butanol olfactory sensitivity. Furthermore, women who were particularly sensitive to the taste of oleic acid had less restraint in their eating habits and higher BMIs. High olfactory sensitivity to oleic acid was substantially linked with dietary consumption of nut spreads, nuts, and seeds. The authors comment that these results show a distinct relationship between fatty acid taste sensitivity and olfaction and imply that the perception of fat is linked to specific traits of eating behavior and body composition. [NPID: Fatty acid taste, olfaction, sensory, mouthfeel, test-retest, eating behavior, dietary intake, BMI, taste]

Rodent eating behavior is regulated by post-ingestive nutritional signals to the brain, and disordered eating behavior and obesity have been linked to inadequate responses to these signals. In this study by van Galen et al. (2023), the authors conducted a single-blinded, randomized, controlled, crossover research in 30 healthy people (females N = 12, men N = 18) and 30 people who were obese (females N = 18, males N = 12). Observations were made on the impact of intragastric infusions of glucose, fat, and water (noncaloric isovolumetric control) firstly on striatal dopamine release and cerebral neuronal activity and the secondary endpoints of plasma hormones and glucose, caloric intake, and hunger scores. Imaging was performed following a 10% diet-induced weight loss to examine if the decreased responses in obese people might be partially reversible. Analysis of the results demonstrated that, in lean volunteers, intragastric glucose and lipid infusions resulted in nutrient-specific cerebral neuronal activity and striatal dopamine release, which were orosensory-independent and preference-independent. Participants that are obese, however, showed dramatically hampered brain reactions to nutrients post-ingestion. Finally, diet-induced weight loss was not found to repair the altered neuronal responses. The authors conclude that overeating and obesity may be caused by impaired neuronal responses to nutritional cues, and the high rate of weight gain following a successful weight reduction effort may be partially explained by continued resistance to post-ingestive food signals after significant weight loss. [NPID: Brain, diet, nutrition signals, obesity, neuronal response, weight loss]

Human relationships and gut microbes are inextricably linked. What we consume reflects our relationship with our body and mind and harmonizes with those around us. However, it has yet to be investigated how this affects the gut microbiota or how gut bacteria affect our food habits. In this study by Di Stefano et al. (2019), the authors investigate the "gut-human behavior axis" and its evolutionary dynamics in a real-world situation represented by the social multiplex network to quantify the complicated dynamics of this interaction between gut and human behaviors. In addition to psychological and unconscious biases, this interplay was analyzed under two types of resemblance: homophily and gut similarity. The effect of human actions on diets and gut microbial composition was measured both ways using a control mechanism in terms of the dynamics of social and gut microbial communities. Along with the type and amount of food consumed, meal timing mechanisms and "chrono-nutrition" are essential factors in eating behavior. The authors investigated the dynamic interaction between shift workers' eating habits and gut flora by simulating the social dynamics of chrono-nutrition in a multiplex network. The authors comment that their findings enable methodologically introducing gut metabolic models and statistical estimators, capable of capturing their dynamic interaction, to quantify the relationship between human behaviors and gut microbiota. Additionally, analysis of the results revealed that shift work has an influence on the dynamics of chrono-nutrition in the form of a fluctuation in behavioral strategies with a high tendency for defection (such as high-fat meals) and that the timing of gut microbial populations is slower than social interactions and shift work. The authors discuss that it is possible to improve our understanding of metabolic models and their impacts on human health by developing a deeper understanding of the links between gut microbiota and dietary behavioral patterns and incorporating related social aspects, thereby enabling the development of effective social therapeutic nutritional interventions. [NPID: Gastrointestinal microbiome, feeding behavior, metabolome, biological model, shift work, social behavior, time factors]

The use of mobile phones has followed similar trends to the prevalence of obesity across the world. Mobile phones emit radio frequency-modulated electromagnetic fields (RF-EMFs) that predominantly bombard the user’s head, leading to alterations in brain glucose metabolism and neuronal excitability. On the other hand, the brain is also responsible for regulating food intake and the perception of appetite through the hypothalamus, thereby adjusting overall body weight. Wardzinski et al. (2022) conducted this single-blind, sham-controlled randomized crossover study to investigate whether the radiation emitted by mobile phones influence food intake. The study participants (n = 15 healthy males, age = 23.47 ± 0.68 years) were fasted prior to exposure to either 25 minutes of RF-EMFs from two mobile phones, or to sham radiation. Thereafter, their food intake was evaluated through a standard buffet test (ad libitum), and had their brain energy homeostasis investigated using 31phosphorus-magnetic resonance spectroscopy. Analysis of the participants revealed an increase in caloric intake with mobile phone usage by 22-27% compared to sham controls, attributed for the most part to an increase in carbohydrate consumption. A rise in cerebral energy (demonstrated through phosphocreatine and adenosine triphosphate levels versus inorganic phosphate) was also observed in participants exposed to mobile phone radiation. The authors conclude that RF-EMFs may enhance overeating and promote obesity, and that RF-EMFs should be further investigated to understand its effects on brain homeostasis and functions [NPID: Body weight, brain, food intake, mobile phone, electromagnetic fields]

In this 2021 study, participants were randomized to a 12-week or 52-week behavioral weight management intervention or a brief self-help intervention. The objective was to determine if hedonic hunger decreases during this behavioral weight management program. Another target was to find out if hedonic hunger predicts BMI. The participants were UK-based adults, mostly with obesity (82.5%). The results revealed that hedonic hunger decreased at the 3-month point of the intervention, and this reduction remained at 24 months. Higher hedonic hunger scores at 3 months predicted higher BMI at 12 months but not at 24 months. After 12 months, the participants taking part in the 52-week behavioral weight management intervention had lower BMI than those participating in the 12-week program as well as those in the brief self-help intervention program. Hedonic hunger dropped during the weight management program irrespective of which intervention. The early reductions in hedonic hunger appeared to be related to lower BMI in the medium term. [NPID: hedonic hunger, BMI, weight management, behavior, UK]

This 2017 study investigated the effect of different food stimuli on people’s visual attention to food. A mobile eye tracking device was used to monitor visual attention while looking at various food pictures varying in calorie content. Attention was specifically measured by analyzing the fixation duration, fixation counts, and visit counts. The results demonstrated a higher level of visual attention towards cut up, ready-to-eat low-calorie foods when compared with both savory and sweet high-calorie foods. Men were found to pay more attention to high-calorie food items, while women focused on low-calorie foods more. It appeared that people’s attention varies depending on the type of food stimuli presented. The attention of men and women tend to be drawn to different types of food stimuli. These results may have implications for food marketing and healthcare promotion campaigns. [NPID: behavior, food stimuli, food cues, visual attention, calorie content, diet, nutrition]

This 2019 study evaluated long-haul truck drivers on their food choice patterns since there was limited data on truck drivers driving through Europe. The aim was to compare their dietary choices while working versus while at home. Questionnaires were handed out in 12 different languages at two truck stops in Germany. The survey determined that only 24% of the 404 truck drivers who responded were of normal body weight, while 46% were considered overweight and 30% obese. More than half of the participants were smokers, and 32% reported at least one chronic disease. With regards to eating habits, 37% of the truck drivers ate their meals often or always at truck stops, while 6% never did so. The long-distance drivers most brought fruits (62%) and sausages (50.6%) on their drives. The next most common food items were sandwiches (38.7%), self-cooked meals (37%), sweets (35.4%), and raw vegetables (31%). Compared to in the house, the participants consumed more sausages, energy drinks, soft drinks, and canned foods during their work trips. At home, fresh vegetables, legumes and fish were more often chosen. Food choice patterns and food preparation did not differ significantly across weight categories. But a link was found between food choice patterns and the available food appliances in trucks. To conclude, the working conditions of long-haul truck drivers influence food choices during work and make a healthy lifestyle difficult to follow. [NPID: eating behavior, truck drivers, working conditions, food choice, diet, occupational health, overweight, obesity]

The objective of this 2018 study was to examine if there is a correlation between patterns in eating behaviors with visual attention to food cues. This article also considered the effect of gender in this equation. Mobile eye tracking technology was used to measure visual attention to food cues, while the Dutch Eating Behavior Questionnaire (DEBQ) was applied to determine participants’ eating behavior patterns (where it be restrained, emotional, or external eating). The results revealed the influential effect of restrained eating behavior on visual attention. Moreover, men who showed higher degrees of restrained eating behavior also paid more attention to low-calorie food cues. Women, on the other hand, had a notable association with emotional eating behavior. The women with higher levels of emotional eating behaviors were found to pay more visual attention to food cues. This study highlights the potential effect of gender on relationships between eating behavior and visual attention. [NPID: eating behavior, gender, visual attention, restrained eating, emotional eating, food calories]

Since there is inconsistent data on the link between breakfast consumption and overweight/obesity, this 2020 systematic review and meta-analysis was conducted on observational studies pertinent to the breakfast-weight status association. This article specifically searched for cohort and cross-sectional studies that reported either odds or risk ratio estimates for the association between breakfast skipping and overweight/obesity. In total there were 45 studies included in the meta-analysis, including 36 cross-sectional and 9 cohort studies. Compiling data from the cross-sectional studies, participants who had breakfast less frequently during the week were 48% more likely to be overweight/obese, and showed a 31% higher risk of abdominal obesity, when compared with those who frequently had breakfast. Even in the cohort studies, the low-frequency breakfast consumers were at greater risk of being overweight or obese (relative to high-frequency breakfast consumers). Considering these consistent results in cross-sectional and cohort studies, this meta-analysis concludes that skipping breakfast increases the risk of, and is associated with, overweight/obesity. There is no notable difference in trends among different ages, gender, geography, and economic conditions. [NPID: breakfast, diet, habits, eating, behaviors, behaviours, obesity, obese, overweight, review, meta-analysis, skipping breakfast]

This 2014 was the first in its time to investigate hedonic hunger (appetitive drive to eat for pleasure rather than hunger) among individuals with eating disorders. Hedonic hunger has been associated with overeating and uncontrolled overeating. Witt & Lowe therefore gathered a sample of patients with anorexia nervosa, restricting type (AN-R), anorexia nervosa, binge-purge type (AN-B/P), and bulimia nervosa (BN), and assessed the participants on hedonic hunger using the Power of Food Scale (PFS). The aims of the study included evaluating the relationship between PFS scores and frequency of binge eating and determining whether baseline PFS scores could be used to predict weight change during treatment. Individuals with bulimia nervosa scored higher on the PFS (hedonic hunger measure) compared to anorexia nervosa sufferers of either type (restricting and binge-purge), although those with binge-purge type appeared to score higher than than those with restring type anorexia. In uncontrolled and controlled analysis models, greater PFS scores were found to correlate with more frequent binge eating among patients with bulimia. A similar pattern was also observed among subjects with anorexia. Finally, PFS scores predicted alterations in weight in anorexic participants but not in bulimic patients. These findings suggest that hedonic processes may have vital roles in triggering binge eating, and that there may be potential in managing hedonic appetite in weight management among people with anorexia. [NPID: craving, hedonic hunger, appetite, eating disorders, overeating, binge eating, anorexia, bulimia]

This 2018 study applied the cognitive processing model of alcohol craving (CPMA) while investigating the role of food craving in the already well-established restrained eating–overeating relationship linked with binge eating disorder (BED). A sample of 1058 respondents completed an online survey assessing restrained eating, trait food craving, uncontrolled eating, and emotional eating. After implementing the CPMA, food craving was found to significantly affect, in an indirect manner, the association between restrained eating and both uncontrolled and emotional eating. Gender did not appear to influence the dynamics between restrained eating and different facets of overeating. This study has indicated that to target binge eating behaviors, it may be more effective to give consideration to the activation of food craving rather than to the reduction of restrained eating. Moreover, Verzijl et al. have uncovered that food craving is a target with potential to cut down people’s binge and overeating behaviors, regardless of the person’s gender. [NPID: craving, behavior, CPMA, binge eating, restrained eating, trait food craving, uncontrolled eating, emotional eating, overeating]

This 2021 study investigated whether total negative affect per day and level of negative affect variability per day possess influence on the likelihood of the individual eating high-calorie snacks in the presence of snacking cues. The data was extracted from an ecological momentary assessment study which took food logs and tested their 60 participants for 14 days using known snack cues. As with previous studies, the chances of the subject consuming a snack increased when food was available, when others were eating, and when higher negative affect was experienced. These associations between snack consumption with food availability and presence of others eating were significantly moderated by negative affect variability. In other words, correlations between snack cues and high-calorie snacking were weaker on days of higher negative affect variability. However, negative affect levels did not moderate the relationship between cue and snacking. In conclusion, variability in negative affect can have an influence on the snacking cue-behavior interaction. A complex relationship is suggested here between negative affect and calorie-dense snacking, perhaps requiring clearer conceptualizations. [NPID: behavior, negative affect, affect, food cues, snacking cues, snack cues]

Meule & Kübler (2012) highlight the increasing amount of evidence being released suggesting that food cravings and excessive food intake are due to addictive processes. This present study administered the Yale Food Addiction Scale (YFAS), a novel measure for identifying those with addictive dietary patterns. The respondents of this online study completed this YFAS as well as the Food Cravings Questionnaire-Trait (FCQ-T). Those participants diagnosed with food addiction according to the YFAS had higher scores on all food craving subscales except for anticipation of positive reinforcement (which was thought to perhaps come as a result of eating). Analysis models later indicated positive correlations between all the food craving subscales with food addiction symptoms, while positive reinforcement could negatively predict signs of food addiction. This study therefore demonstrates that people with addictive eating patterns feel more food cravings but do not expect positive reinforcement through eating. [NPID: behavior, cravings, addiction, positive reinforcement]